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This book provides managers and professionals with the necessary approaches for designing software and hardware architectures that support data platform organizations, specifically how to achieve hyper-automation that requires the decomposition of existing platforms to smaller parts that can reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases will allow those with data-centric minds to pursue actions that can better predict and respond to the unexpected. Indeed, most existing companies are struggling because of the lack of best practices to move product departments to independent platforms that can be retrofitted to form new products dynamically based on consumer demands. Featuring exercises at the end of each chapter and online ancillary materials, this book is appropriate for C-level executives engaged in the digital transformation of their firms; entrepreneurs that are planning on forming digital platform companies; and senior software engineers that need to understand how to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate level professional university coursework in data science.
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